Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis

Developmental trajectory and sex differences in auditory processing in a PTEN-deletion model of autism spectrum disorders

Autism Spectrum Disorders (ASD) encompass a wide array of debilitating symptoms, including severe sensory deficits and abnormal language development. Sensory deficits early in development may lead to broader symptomatology in adolescents and adults. The mechanistic links between ASD risk genes, sensory processing and language impairment are unclear. There is also a sex bias in ASD diagnosis and symptomatology. The current study aims to identify the developmental trajectory and genotype- and sex-dependent differences in auditory sensitivity and temporal processing in a Pten-deletion (phosphatase and tensin homolog missing on chromosome 10) mouse model of ASD. Auditory temporal processing is crucial for speech recognition and language development and deficits will cause language impairments. However, very little is known about the development of temporal processing in ASD animal models, and if there are sex differences. To address this major gap, we recorded epidural electroencephalography (EEG) signals from the frontal (FC) and auditory (AC) cortex in developing and adult Nse-cre PTEN mice, in which Pten is deleted in specific cortical layers (layers III-V) (PTEN conditional knock-out (cKO). We quantified resting EEG spectral power distribution, auditory event related potentials (ERP) and temporal processing from awake and freely moving male and female mice. Temporal processing is measured using a gap-in-noise-ASSR (auditory steady state response) stimulus paradigm. The experimental manipulation of gap duration and modulation depth allows us to measure cortical entrainment to rapid gaps in sounds. Temporal processing was quantified using inter-trial phase clustering (ITPC) values that account for phase consistency across trials. The results show genotype differences in resting power distribution in PTEN cKO mice throughout development. Male and female cKO mice have significantly increased beta power but decreased high frequency oscillations in the AC and FC. Both male and female PTEN cKO mice show diminished ITPC in their gap-ASSR responses in the AC and FC compared to control mice. Overall, deficits become more prominent in adult (p60) mice, with cKO mice having significantly increased sound evoked power and decreased ITPC compared to controls. While both male and female cKO mice demonstrated severe temporal processing deficits across development, female cKO mice showed increased hypersensitivity compared to males, reflected as increased N1 and P2 amplitudes. These data identify a number of novel sensory processing deficits in a PTEN-ASD mouse model that are present from an early age. Abnormal temporal processing and hypersensitive responses may contribute to abnormal development of language function in ASD.

Negative emotions reduce sensorimotor cortex activity during proprioceptive modulation of rolandic ∼20HZ beta rhythm in typically developing children and those with neurodevelopmental conditions

BACKGROUND

The Rolandic ∼20-Hz beta rhythm of the sensorimotor cortex is associated with motor function and perception. However, the modulation of this rhythm by different emotional stimuli is an innovative area of research.

AIMS

This study aims at investigating the impact of affective pictures (positive, negative, and neutral) on the proprioceptive modulation of the Rolandic ∼20 Hz beta rhythm in typically developing children and children with neurodevelopmental disorders (i.e. cerebral palsy and autism).

METHODS AND PROCEDURES

EEG was recorded while participants experienced passive wrist movements during the simultaneous viewing of affective pictures. Time-frequency analysis of the sensorimotor oscillatory activity was performed.

OUTCOMES AND RESULTS

Our findings revealed that pictures with negative emotional valence notably diminish event-related synchronization (ERS) amplitude during the perception of hand movement in all groups of children.

CONCLUSIONS AND IMPLICATIONS

These findings suggest that emotional stimuli, particularly the negative ones, could significantly influence brain's processing of proprioception, adding knowledge to the interaction of common comorbidities, such as sensorimotor disorders and emotional dysregulation, in children with neurodevelopmental disabilities.

Quantifying instability in neurological disorders EEG based on phase space DTM function

Classifying individuals with neurological disorders and healthy subjects using EEG is a crucial area of research. The current feature extraction approach focuses on the frequency domain features in each of the EEG frequency bands and functional brain networks. In recent years, researchers have discovered and extensively studied stability differences in the electroencephalograms (EEG) of patients with neurological disorders. Based on this, this paper proposes a feature descriptor to characterize EEG instability. The proposed method starts by forming a signal point cloud through Phase Space Reconstruction (PSR). Subsequently, a pseudo-metric space is constructed, and pseudo-distances are calculated based on the consistent measure of the point cloud. Finally, Distance to Measure (DTM) Function are generated to replace the distance function in the original metric space. We calculated the relative distances in the point cloud by measuring signal similarity and, based on this, summarized the point cloud structures formed by EEG with different stabilities after PSR. This process demonstrated that Multivariate Kernel Density Estimation (MKDE) based on a Gaussian kernel can effectively separate the mappings of different stable components within the signal in the phase space. The two average DTM values are then proposed as feature descriptors for EEG instability.In the validation phase, the proposed feature descriptor is tested on three typical neurological disorders: epilepsy, Alzheimer's disease, and Parkinson's disease, using the Bonn dataset, CHB-MIT, the Florida State University dataset, and the Iowa State University dataset. DTM values are used as feature inputs for four different machine learning classifiers, and The results show that the best classification accuracy of the proposed method reaches 98.00 %, 96.25 %, 96.71 % and 95.34 % respectively, outperforming commonly used nonlinear descriptors. Finally, the proposed method is tested and analyzed using noisy signals, demonstrating its robustness compared to other methods.

A longitudinal study of breastmilk feeding duration, EEG power and early academic skills

BACKGROUND

The cognitive benefits of breastfeeding are widely recognized; however, its effects on brain development and later academic skills require further examination. This study aimed to examine the longitudinal relations between breastmilk feeding, neurophysiological changes, and early academic skills.

METHODS

In the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort, breastmilk feeding practices were collected every 3 months from 3 weeks to 18 months postpartum. Resting electroencephalography (EEG) was recorded at 18 months and power spectral density was derived. The outcomes were a set of early academic assessments administered at age 4 (n = 810). Structural equation modelling was used to investigate EEG power as a mediator between breastmilk duration and early academic skills.

RESULTS

Breastmilk feeding for ≥12 months was associated with better general knowledge, numeracy, and language at age 4 compared to shorter durations of breastmilk feeding (Cohen's d: 1.53-17.44). Linear regression showed that breastmilk duration was negatively and positively associated with low- (i.e., delta, theta) and high-frequency power (i.e., gamma), respectively (Cohen's f2: 0.03-0.09). After adjusting for demographic and child baseline covariates, a decrease in absolute and relative delta, as well as relative theta was associated with better general knowledge and numeracy (Cohen's f2: 0.16-0.25). Relative delta power provided an indirect path between breastmilk duration and early academic skills (x2: 18.390, p = 0.010; CFI: 0.978; TLI: 0.954; RMSEA: 0.040).

CONCLUSIONS

Extended breastmilk feeding is associated with reduced low-frequency power and better early academic skills, suggesting benefits to brain development. Additional research to confirm this finding is warranted.

EEG Techniques with Brain Activity Localization, Specifically LORETA, and Its Applicability in Monitoring Schizophrenia

Background/Objectives: Electroencephalography (EEG) is considered a standard but powerful tool for the diagnosis of neurological and psychiatric diseases. With modern imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and magnetoencephalography (MEG), source localization can be improved, especially with low-resolution brain electromagnetic tomography (LORETA). The aim of this review is to explore the variety of modern techniques with emphasis on the efficacy of LORETA in detecting brain activity patterns in schizophrenia. The study's novelty lies in the comprehensive survey of EEG methods and detailed exploration of LORETA in schizophrenia research. This evaluation aligns with clinical objectives and has been performed for the first time. Methods: The study is split into two sections. Part I examines different EEG methodologies and adjuncts to detail brain activity in deep layers in articles published between 2018 and 2023 in PubMed. Part II focuses on the role of LORETA in investigating structural and functional changes in schizophrenia in studies published between 1999 and 2024 in PubMed. Results: Combining imaging techniques and EEG provides opportunities for mapping brain activity. Using LORETA, studies of schizophrenia have identified hemispheric asymmetry, especially increased activity in the left hemisphere. Cognitive deficits were associated with decreased activity in the dorsolateral prefrontal cortex and other areas. Comparison of the first episode of schizophrenia and a chronic one may help to classify structural change as a cause or as a consequence of the disorder. Antipsychotic drugs such as olanzapine or clozapine showed a change in P300 source density and increased activity in the delta and theta bands. Conclusions: Given the relatively low spatial resolution of LORETA, the method offers benefits such as accessibility, high temporal resolution, and the ability to map depth layers, emphasizing the potential of LORETA in monitoring the progression and treatment response in schizophrenia.

Oscillatory activity underlying cognitive performance in children and adolescents with autism: a systematic review

Autism spectrum disorder (ASD) is a neurodevelopmental condition that exhibits a widely heterogeneous range of social and cognitive symptoms. This feature has challenged a broad comprehension of this neurodevelopmental disorder and therapeutic efforts to address its difficulties. Current therapeutic strategies have focused primarily on treating behavioral symptoms rather than on brain psychophysiology. During the past years, the emergence of non-invasive brain stimulation techniques (NIBS) has opened alternatives to the design of potential combined treatments focused on the neurophysiopathology of neuropsychiatric disorders like ASD. Such interventions require identifying the key brain mechanisms underlying the symptomatology and cognitive features. Evidence has shown alterations in oscillatory features of the neural ensembles associated with cognitive functions in ASD. In this line, we elaborated a systematic revision of the evidence of alterations in brain oscillations that underlie key cognitive processes that have been shown to be affected in ASD during childhood and adolescence, namely, social cognition, attention, working memory, inhibitory control, and cognitive flexibility. This knowledge could contribute to developing therapies based on NIBS to improve these processes in populations with ASD.